{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pima Indians Diabetes Data Set数据探索\n",
    "\n",
    "数据说明：\n",
    "Pima Indians Diabetes Data Set（皮马印第安人糖尿病数据集） 根据现有的医疗信息预测5年内皮马印第安人糖尿病发作的概率。  \n",
    "数据集共9个字段:  \n",
    "0列为pregnants(怀孕次数)；  \n",
    "1列为Plasma_glucose_concentration(口服葡萄糖耐量试验中2小时后的血浆葡萄糖浓度)；  \n",
    "2列为blood_pressure(舒张压,单位:mm Hg）  \n",
    "3列为Triceps_skin_fold_thickness(三头肌皮褶厚度,单位：mm）  \n",
    "4列为serum_insulin(餐后血清胰岛素,单位:mm）  \n",
    "5列为BMI,体重指数（体重（公斤）/ 身高（米）^2）  \n",
    "6列为Diabetes_pedigree_function(糖尿病家系作用)   \n",
    "7列为Age(年龄)\n",
    "8列为Target(分类变量,0或1）  \n",
    "数据链接：https://archive.ics.uci.edu/ml/datasets/Pima+Indians+Diabetes  \n",
    "Kaggle也有一个Practice Fusion Diabetes Classification任务，可以试试:) https://www.kaggle.com/c/pf2012-diabetes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. import 工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#首先 import 必要的模块\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "#color = sns.color_palette()\n",
    "%matplotlib inline\n",
    "#忽略warning的输出\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pregnants</th>\n",
       "      <th>Plasma_glucose_concentration</th>\n",
       "      <th>blood_pressure</th>\n",
       "      <th>Triceps_skin_fold_thickness</th>\n",
       "      <th>serum_insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Diabetes_pedigree_function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   pregnants  Plasma_glucose_concentration  blood_pressure  \\\n",
       "0          6                           148              72   \n",
       "1          1                            85              66   \n",
       "2          8                           183              64   \n",
       "3          1                            89              66   \n",
       "4          0                           137              40   \n",
       "\n",
       "   Triceps_skin_fold_thickness  serum_insulin   BMI  \\\n",
       "0                           35              0  33.6   \n",
       "1                           29              0  26.6   \n",
       "2                            0              0  23.3   \n",
       "3                           23             94  28.1   \n",
       "4                           35            168  43.1   \n",
       "\n",
       "   Diabetes_pedigree_function  Age  Target  \n",
       "0                       0.627   50       1  \n",
       "1                       0.351   31       0  \n",
       "2                       0.672   32       1  \n",
       "3                       0.167   21       0  \n",
       "4                       2.288   33       1  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#input data\n",
    "train = pd.read_csv(\"pima-indians-diabetes.csv\")\n",
    "#scan 5 line\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train : (768, 9)\n"
     ]
    }
   ],
   "source": [
    "#查看数据集的形状\n",
    "print(\"Train :\", train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 9 columns):\n",
      "pregnants                       768 non-null int64\n",
      "Plasma_glucose_concentration    768 non-null int64\n",
      "blood_pressure                  768 non-null int64\n",
      "Triceps_skin_fold_thickness     768 non-null int64\n",
      "serum_insulin                   768 non-null int64\n",
      "BMI                             768 non-null float64\n",
      "Diabetes_pedigree_function      768 non-null float64\n",
      "Age                             768 non-null int64\n",
      "Target                          768 non-null int64\n",
      "dtypes: float64(2), int64(7)\n",
      "memory usage: 54.1 KB\n"
     ]
    }
   ],
   "source": [
    "#查看数据基本信息\n",
    "#total values in each column, null/not null, datatype, memory occupied etc\n",
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pregnants                       111\n",
      "Plasma_glucose_concentration      5\n",
      "blood_pressure                   35\n",
      "Triceps_skin_fold_thickness     227\n",
      "serum_insulin                   374\n",
      "BMI                              11\n",
      "Diabetes_pedigree_function        0\n",
      "Age                               0\n",
      "Target                          500\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print((train == 0).sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在一些特定列代表的变量中，0值并没有意义，这就表名该值无效或为缺失值。  \n",
    "具体来说下列变量的最小值为0时数据无意义：  \n",
    "1.Plasma_glucose_concentration(口服葡萄糖耐量试验中2小时后的血浆葡萄糖浓度)；  \n",
    "2.blood_pressure(舒张压,单位:mm Hg）  \n",
    "3.Triceps_skin_fold_thickness(三头肌皮褶厚度,单位：mm）  \n",
    "4.serum_insulin(餐后血清胰岛素,单位:mm）  \n",
    "5.BMI,体重指数（体重（公斤）/ 身高（米）^2）\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pregnants</th>\n",
       "      <th>Plasma_glucose_concentration</th>\n",
       "      <th>blood_pressure</th>\n",
       "      <th>Triceps_skin_fold_thickness</th>\n",
       "      <th>serum_insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Diabetes_pedigree_function</th>\n",
       "      <th>Age</th>\n",
       "      <th>Target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        pregnants  Plasma_glucose_concentration  blood_pressure  \\\n",
       "count  768.000000                    768.000000      768.000000   \n",
       "mean     3.845052                    120.894531       69.105469   \n",
       "std      3.369578                     31.972618       19.355807   \n",
       "min      0.000000                      0.000000        0.000000   \n",
       "25%      1.000000                     99.000000       62.000000   \n",
       "50%      3.000000                    117.000000       72.000000   \n",
       "75%      6.000000                    140.250000       80.000000   \n",
       "max     17.000000                    199.000000      122.000000   \n",
       "\n",
       "       Triceps_skin_fold_thickness  serum_insulin         BMI  \\\n",
       "count                   768.000000     768.000000  768.000000   \n",
       "mean                     20.536458      79.799479   31.992578   \n",
       "std                      15.952218     115.244002    7.884160   \n",
       "min                       0.000000       0.000000    0.000000   \n",
       "25%                       0.000000       0.000000   27.300000   \n",
       "50%                      23.000000      30.500000   32.000000   \n",
       "75%                      32.000000     127.250000   36.600000   \n",
       "max                      99.000000     846.000000   67.100000   \n",
       "\n",
       "       Diabetes_pedigree_function         Age      Target  \n",
       "count                  768.000000  768.000000  768.000000  \n",
       "mean                     0.471876   33.240885    0.348958  \n",
       "std                      0.331329   11.760232    0.476951  \n",
       "min                      0.078000   21.000000    0.000000  \n",
       "25%                      0.243750   24.000000    0.000000  \n",
       "50%                      0.372500   29.000000    0.000000  \n",
       "75%                      0.626250   41.000000    1.000000  \n",
       "max                      2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看数值型特征的基本统计量\n",
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plasma_glucose_concentration      5\n",
      "blood_pressure                   35\n",
      "Triceps_skin_fold_thickness     227\n",
      "serum_insulin                   374\n",
      "BMI                              11\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "NaN_col_names = ['Plasma_glucose_concentration','blood_pressure','Triceps_skin_fold_thickness','serum_insulin','BMI']\n",
    "print((train[NaN_col_names] == 0).sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "第1、2、5列中0值较少；相比较而言，第3、4列中的0值多出数倍，接近总量的一半。 为了确保有足够的数据量来训练模型，针对不同的列需要有不同的缺失值判断策略。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 查看每个变量的分布及其与标签之间的关系"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分类Target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Number of occurrences')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#该问题为分类问题，类别型特征直方图可用countplot\n",
    "sns.countplot(train['Target'])\n",
    "plt.xlabel('Diabetes')\n",
    "plt.ylabel('Number of occurrences')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 怀孕次数pregnants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Number of occurrences')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "### Number of occurrences\n",
    "sns.countplot(train['pregnants'])\n",
    "plt.xlabel('Number of pregnants',fontsize=14)\n",
    "plt.ylabel('Number of occurrences',fontsize=14)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 剔除异常值，删除怀孕次数大于等于10的样本"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(710, 9)\n"
     ]
    }
   ],
   "source": [
    "#怀孕次数有超过17的？\n",
    "#但在疾病判断案例中，异常值可能就意味着得病，不能删除\n",
    "ulimit = 10\n",
    "\n",
    "#删除怀孕次数大于等于10的样本\n",
    "train = train[train['pregnants'] < ulimit]\n",
    "print (train.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 怀孕次数pregnants与得病分类Target的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f036fffb080>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"pregnants\", hue=\"Target\",data=train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "随着怀孕次数的增加，样本中生病与不生病的人数的比值也逐渐增加，说明怀孕次数在比较大的情况下，和是否生病有关系"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  血浆葡萄糖浓度Plasma_glucose_concentration\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Number of occurrences')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "#数值型特征用distplot\n",
    "sns.distplot(train.Plasma_glucose_concentration, kde = False)\n",
    "plt.xlabel('Plasma_glucose_concentration')\n",
    "plt.ylabel('Number of occurrences')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Plasma_glucose_concentration与Target的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(7,5))\n",
    "sns.violinplot(x='Target', y='Plasma_glucose_concentration', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes Target', fontsize=14)\n",
    "plt.ylabel('Plasma_glucose_concentration', fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  血压blood_pressure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'frequency')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(6,4))\n",
    "sns.distplot(train.blood_pressure, kde = False)\n",
    "plt.xlabel('blood_pressure',fontsize=14)\n",
    "plt.ylabel('frequency',fontsize=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 查看blood_pressure与目标标签Target之间的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x='Target', y='blood_pressure', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=14)\n",
    "plt.ylabel('blood_pressure', fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Triceps_skin_fold_thickness\n",
    "三头肌皮褶厚度（单位：mm）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'frequency')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.Triceps_skin_fold_thickness, kde = False)\n",
    "plt.xlabel('Triceps_skin_fold_thickness',fontsize=14)\n",
    "plt.ylabel('frequency',fontsize=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "看起来这个功能中有一些异常值。所以让我们把它们移走，然后再画图一次。但在疾病判决案中，异常值可能就意味着得病，不能删除  \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ulimit = 80 \n",
    "#train = train[train['Triceps_skin_fold_thickness'] < ulimit]\n",
    "#plt.scatter(range(train.shape[0]), train[\"Triceps_skin_fold_thickness\"].values,color='purple') \n",
    "#plt.title(\"Distribution of Triceps_skin_fold_thickness\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Triceps_skin_fold_thickness与Target的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x='Target', y='Triceps_skin_fold_thickness', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('Triceps_skin_fold_thickness', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### serum_insulin\n",
    "餐后血清胰岛素（单位:mm）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'frequency')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.serum_insulin, kde = False)\n",
    "plt.xlabel('serum_insulin',fontsize=14)\n",
    "plt.ylabel('frequency',fontsize=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### serum_insulin与Target之间的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x='Target', y='serum_insulin', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=12)\n",
    "plt.ylabel('serum_insulin', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### BMI\n",
    "体重指数（体重（公斤）/ 身高（米）^2）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'frequency')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.BMI, kde = False)\n",
    "plt.xlabel('BMI')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "BMI=0为缺失值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### BMI与Target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x='Target', y='BMI', data=train, hue=\"Target\")\n",
    "plt.xlabel('Diabetes', fontsize=14)\n",
    "plt.ylabel('BMI', fontsize=14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f036f74b860>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "BMIDF = train.groupby(['BMI', 'Target'])['BMI'].count().unstack('Target').fillna(0)\n",
    "BMIDF[[0,1]].plot(kind='bar', stacked=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Diabetes_pedigree_function糖尿病家系作用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'frequency')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "###Diabetes_pedigree_function，糖尿病家系作用\n",
    "fig = plt.figure()\n",
    "sns.distplot(train.Diabetes_pedigree_function, kde = False)\n",
    "plt.xlabel('Diabetes_pedigree_function')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Diabetes_pedigree_function和Target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f036efd6710>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "DF = train.groupby(['Diabetes_pedigree_function', 'Target'])['Diabetes_pedigree_function'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind='bar', stacked=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'frequency')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(train.Age, kde = False)\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('frequency')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Age和Target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f038b018b00>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "DF = train.groupby(['Age', 'Target'])['Age'].count().unstack('Target').fillna(0)\n",
    "DF[[0,1]].plot(kind='bar', stacked=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 特征之间的相关性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f036e09d438>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_corr = train.corr().abs()\n",
    "\n",
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7VTVTVb8HrgSeNeaaRm5vDnqnWRiQJMyOwW6sqg+Mu55xqqp3VNWKqlrJ7M/FV6qq+au2HamqHwF3JzmyazoZ+PYYSxqnzcCJSfbvfmdOZgl8MD2yJ2NHzWkWHuIk4FXAbUlu6dre2T2hLL0euLi7KLoLeM2Y6xmLqlqf5ArgJmbvVLuZJfCErE/GSlLj9uahG0nSAhj0ktQ4g16SGmfQS1LjDHpJapxBL41YkmOSvHjcdWjpMujVvG6m03E6BjDoNTYGvfZqSVZ2c6yvS3JrN+f6/kl+kOTdSb4GnJbkiUm+lGRDkv9OclS3/xOT3Jjkm0nek+SXXfvzktwwMIf7xd2TlHTv+81uPvO1A+03JDk/yTeSfC/Jc7oHlN4DvCLJLUlekeQvu+VbuknG/mxMp09LhEGvFhwJrK2qpwI/B17Xtf9fVT27qi5l9unH11fV04G3AB/t+lwAXFBVz+ChcyUdC5zL7PcdPIHZp48BPlJVz+jmM38k8NKBfZZV1fHdfud1U2i/G7isqo6pqsu6459dVccAzwF+szinQZqbQa8W3F1VX++WPwM8u1u+DP40o+ezgM9100P8G3Bo1+eZwOe65c9u977fqKrpqvojcAuwsmv/qyTrk9wGPB948sA+WyeT2zDQf3tfBz6Q5A3AAVX1wEL/otIw9tq5bqQB28/jsXX9V93rw4D7uivoXfHbgeU/AMu6r537KLPfUHR3kn8C9ptjnz+wg9+vqnpfkv9kdtz+xiQvqKrv7GJt0oJ5Ra8WHD7wHahnAF8b3NjNy//9JKfB7EyfSZ7Wbb4R+LtueSFfKbc11H/S/U/h5QvY5xfAn8bhkzyxqm6rqvOBKeCoBbyHNDSDXi3YCKxOcitwEHDhHH3OBM5K8i3gDh782slzgTcl+Qazwzn37+xA3VfwfQy4DfgPZqfLns/1wNFbP4wFzu0+yP0Ws+PzX1zAe0hDc/ZK7dW6r038QvfB6DD77w/8pqoqyenAGVW1ZL97WG1yjF5L3dOBj3S3SN4HvHbM9UiLzit6SWqcY/SS1DiDXpIaZ9BLUuMMeklqnEEvSY0z6CWpcf8PhNhQ7x/wj38AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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WN6K0cpa6ThQ/qcmqjiS5CPibJK+a9/iXgQ8CjwM3b0A+aVU4/aITTlX9M7AZmJu376fAfuA9TFatlGaSI3WdcJK8HDiJyeJJp8x76C+Af6iqH0wWsJRmj6WuE8XROXWYfDjFzqp6en55V9V9+K4XzThXaZSkRpxTl6RGLHVJasRSl6RGLHVJasRSl6RGLHVJasRSl6RGLHVJauT/AIIm6/Xd6WeHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for feature in train.columns:\n",
    "    sns.distplot(train[feature],kde = False)\n",
    "    plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
